The aim of this project is to understand the three-dimensional shape perception of patterned surfaces. Extra-striate cortex includes many neurons that are selective to 3-D surface orientation defined by texture cues, but there are no feasible models of neural connections that build such receptive fields. We have shown that to extract 3-D shape from texture, assumptions of texture homogeneity and estimates of texture gradients are not needed. Instead, surface curvature/orientation estimates are provided by orientation flows, and depth estimates by frequency flows. These flows predict both correct perceptions and misperceptions. Since V1 neurons are selective for orientation and frequency, we will build models that combine their outputs to extract orientation and frequency flows for identifying distinct shape features. Experiments will specify the temporal and spatial properties of the neural mechanisms. We will use new types of diagnostic stimuli, without cue conflict, to examine the manner in which motion and texture cues interact in 3-D perception, and whether motion contributes to the perception of intrinsic curvature or just to relative depth. We will analyze shading patterns on naturalistic textured objects in terms of orientation flows and frequency gradients. We will see how these aspects of shading interact in 3-D perception, with orientation and frequency information from textures. We will examine how texture and silhouette cues interact to explain some motion and shape illusions with real 3-D solids. We will test whether neural mechanisms for shape-from texture are hard-wired or can be altered by experience, by using haptic feedback to correct misperceptions from texture cues. This study will show how simple neural connections lead to complex 3-D percepts. These results will be useful both in understanding the causes of neurological deficits in shape perception, and in building artificial visual aids for patients with such deficits.